A5016153537- Neuroscience and Neural Engineering
- Neural dynamics and brain function
- 3D Printing in Biomedical Research
- Functional Brain Connectivity Studies
- Advanced Memory and Neural Computing
- EEG and Brain-Computer Interfaces
- Neuroscience and Neuropharmacology Research
- Memory and Neural Mechanisms
- Pluripotent Stem Cells Research
- Cell Image Analysis Techniques
- Advanced MRI Techniques and Applications
- Sleep and Wakefulness Research
- Neural Networks and Applications
- Planarian Biology and Electrostimulation
- Digital Imaging for Blood Diseases
- Photoreceptor and optogenetics research
- Brain Tumor Detection and Classification
- Gene Regulatory Network Analysis
- stochastic dynamics and bifurcation
- Autism Spectrum Disorder Research
- Neuroinflammation and Neurodegeneration Mechanisms
- RNA Research and Splicing
- RNA modifications and cancer
- Cellular Mechanics and Interactions
- Neurological disorders and treatments
ETH Zurich
2020-2024
Institute of Molecular and Clinical Ophthalmology Basel
2023
University of Cambridge
2015-2020
Max Planck Institute of Psychiatry
2010-2015
Zero to Three
2013
Neurology, Inc
2012
Max Planck Society
2011
Graph theoretical analysis of functional magnetic resonance imaging (fMRI) time series has revealed a small-world organization slow-frequency blood oxygen level-dependent (BOLD) signal fluctuations during wakeful resting. In this study, we used graph measures to explore how physiological changes sleep are reflected in connectivity and network properties large-scale, low-frequency brain network. Twenty-five young healthy participants fell asleep 26.7 min fMRI scan with simultaneous...
In imaging functional connectivity (FC) analyses of the resting brain, alterations FC during unconsciousness have been reported. These results are in accordance with recent electroencephalographic studies observing impaired top-down processing anesthesia. this study, simultaneous records magnetic resonance (fMRI) and electroencephalogram were performed to investigate causality neural mechanisms propofol-induced loss consciousness by correlating fMRI directional (DC)...
Abstract In a temporal difference learning approach of classical conditioning, theoretical error signal shifts from outcome deliverance to the onset conditioned stimulus. Omission an expected results in negative prediction signal, which is initial step towards successful extinction and may therefore be relevant for fear recall. As studies rodents have observed bidirectional relationship between rapid eye movement (REM) sleep, we aimed test hypothesis that REM sleep deprivation impairs recall...
Applying graph theoretical analysis of spontaneous BOLD fluctuations in functional magnetic resonance imaging (fMRI), we investigated whole-brain connectivity 11 healthy volunteers during wakefulness and propofol-induced loss consciousness (PI-LOC). After extraction regional fMRI time series from 110 cortical subcortical regions, applied a maximum overlap discrete wavelet transformation changes the brain's intrinsic spatiotemporal organization. During PI-LOC, observed breakdown...
Abstract Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying function. Current labeling and optical methods, however, cannot be used for continuous long-term recordings the dynamics evolution networks, as fluorescent indicators can cause phototoxicity. Here, we introduce a versatile platform label-free, comprehensive detailed electrophysiological live-cell various neurogenic cells tissues over extended time scales. We report on dual-mode...
Recent advances in the field of cellular reprogramming have opened a route to studying fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means study neuronal physiology at different scales, ranging from network through single-neuron subcellular features. In this work, HD-MEAs are used vitro characterize and compare human induced-pluripotent-stem-cell-derived dopaminergic motor neurons, including isogenic lines...
Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has hampered by lack technologies. Here, we adapted retrograde tracing using rabies viruses investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain, engaging in widespread functional communication, cholinergic driving...
Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone the quest develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven phenotyping cultures recorded by high-density microelectrode arrays. DeePhys is modular workflow that offers range techniques extract features from spike-sorted data, allowing examination phenotypes both at individual cell and network levels,...
ABSTRACT Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, precise nature of economic negotiations governing this putative organizational principle remains unclear. Here, we address question further by combining large-scale electrophysiological recordings, to characterize functional connectivity neuronal in vitro , with generative modeling approach capable simulating network formation. We find that best fitting...
Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies neuronal networks at the cellular network scale. Here, we use HD-MEAs derive large-scale recordings from sliced hCOs. We record activity hCO...
Probing the architecture of neuronal circuits and principles that underlie their functional organization remains an important challenge modern neurosciences. This holds true, in particular, for inference connectivity from large-scale extracellular recordings. Despite popularity this approach a number elaborate methods to reconstruct networks, degree which synaptic connections can be reconstructed spike-train recordings alone controversial. Here, we provide framework probe compare algorithms,...
Abstract Patterns of functional interactions across distributed brain regions are suggested to provide a scaffold for the conscious processing information, with marked topological alterations observed in loss consciousness. However, establishing firm link between macro-scale network organisation and cognition requires direct investigations into neuropsychologically-relevant architectural modifications systematic reductions Here we assessed both global regional disturbances graphs group...
Glioblastomas are heterogeneous brain tumors, notorious for their invasive behavior and resistance to therapy. Neuron-to-glioma synapses have been identified promote glioblastoma invasion proliferation. However, a comprehensive characterization of tumor-connected neurons has hampered by lack technologies. Here, we adapted retrograde tracing with modified rabies virus system characterize manipulate connected neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across...
Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between synaptic input patterns spiking output of individual neurons remains largely unresolved. Here, we developed, validated applied a novel vitro experimental platform analytical procedures that provide – simultaneous excitatory inhibitory estimates during network activity. Our approach combines...
Abstract Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between synaptic input patterns spiking output of individual neurons remains largely unresolved. Here, we developed, validated applied a novel vitro experimental platform analytical procedures that provide – simultaneous excitatory inhibitory estimates during network activity. Our approach...
Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying complex activity patterns of biological neuronal networks. In this study, we applied GNNs a large-scale electrophysiological dataset rodent primary networks obtained by means high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording extracellular spiking individual neurons and enable extraction physiologically relevant features at single-neuron population level. We...
Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between synaptic input patterns spiking output of individual neurons remains largely unresolved. Here, we developed, validated applied a novel vitro experimental platform analytical procedures that provide – simultaneous excitatory inhibitory estimates during network activity. Our approach combines...
Abstract Recent advances in the field of cellular reprogramming have opened a route to study fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means neuronal physiology at different scales, ranging from network through single-neuron subcellular features. In this work, we used HD-MEAs vitro characterize and compare human induced-pluripotent-stem-cell (iPSC)-derived dopaminergic motor neurons, including isogenic...
Human brains possess sophisticated information processing capabilities, which rely on the coordinated interplay of billions neurons. Despite recent advances in characterizing collective neuronal dynamics, however, it remains a major challenge to understand principles how functional networks develop and maintain these capabilities. A popular hypothesis is that self-organize critical state [1-3], because models, criticality maximizes capacities [4-6]. This predicts biological should towards...